Download Exploring atmosphere and climate of the Earth using

esa
ACE+
Exploring Atmosphere and Climate
of the Earth
Using
GPS, GALILEO, and LEO-LEO Occultations
Per Høeg (AIR/DMI)
Gottfried Kirchengast (IGAM/UG)
EUMETSAT GRAS SAF 2nd User Workshop 2003
1
esa
Objectives
•
Climate
•
•
Atmosphere
•
•
Observe and analyze globally the
physical condition and state of the
atmosphere of the Earth to improve
predictions of future state
Space Weather
•
EUMETSAT GRAS SAF 2nd User Workshop 2003
Monitoring global long-term
variations in the climate and the
forcings of the atmosphere system
giving rise to trends
Monitoring and modeling of
ionosphere and plasmasphere
electron density structures
2
esa
Primary Issue of Concern: Climate Change
Increasing evidence exists that the Earth’s climate is currently changing (e.g.,
IPCC 2001 Report). The changes are most pronounced in the most variable
component of the Earth system, the atmosphere.
• Key indicators:
• Humidity and temperature in the troposphere tend to increase
• Stratospheric temperatures tend to decrease
• Stratospheric humidity tend to increase with drastic changes in the radiation
• It is likely that these changes are associated with human-induced
increases of greenhouse gas concentrations in the atmosphere.
• Natural variability of the climate system complicates the picture,
rendering proper understanding of climate change very challenging.
EUMETSAT GRAS SAF 2nd User Workshop 2003
3
esa
Variability of Atmospheric Water Vapor
Latitude-Height Slice of Humidity based on ECMWF analysis
Radiosonde Humidity Profile
(15 Sep 1999, 12UTC, 79°W)
(Kauai, Hawaii, 1 Oct 2000, 12UTC)
EUMETSAT GRAS SAF 2nd User Workshop 2003
4
esa
Water Vapor Variability
Column Water Vapor Monthly Map January 1994
EUMETSAT GRAS SAF 2nd User Workshop 2003
Column Water Vapor Monthly Map July 1994
5
esa
Greenhouse Gas Emissions
and Temperature Change Projections
a) CO2 emission paths for several representative
IPCC scenarios
EUMETSAT GRAS SAF 2nd User Workshop 2003
b) Corresponding near surface temperature
change projections
6
esa
Present Observations
Global tropospheric and surface temperature data from different sources
(MSU: MSU satellite data, UKMO: radiosonde-based data, Surface: surface data)
Inset: difference between surface and radiosonde data
EUMETSAT GRAS SAF 2nd User Workshop 2003
7
esa
Scientific Objectives
•
Major goal:
♦
♦
•
Main objectives:
♦
♦
♦
♦
♦
♦
♦
•
Monitor and describe variations and changes in the global atmospheric temperature and water vapor distribution;
Assess climate changes caused by mass field changes and atmosphere dynamics.
To establish highly accurate (< 0.025 g/kg and < 3 % in specific humidity) and vertically resolved (< 1 km) global climatology
of water vapor in the troposphere;
To establish a highly accurate (< 0.2 K) and vertically resolved (~1 km) global climatology of temperature in the troposphere
and the stratosphere;
To perform research on climate variability and climate change together with research in improved atmospheric models as
well as advancements in NWP;
To study troposphere structures in polar and equatorial regions;
To support analysis and validation of data from other space missions;
To demonstrate a new and novel active atmospheric sounding technique with the CALL instrument;
To enhance the European observational capability for improved contribution to the international GCOS initiative.
Advances in atmosphere physics and climate change processes:
♦
♦
♦
♦
♦
♦
♦
Global climate warming and increased averaged atmospheric water vapor levels;
Tropical heat and mass exchange with extra-tropical regions;
Transport across subtropical mixing barriers, relevant for information on the lifetime of greenhouse gases;
Stratospheric winds and temperatures and atmospheric wave phenomena;
Polar front dynamics and mass exchange together with tropospheric water vapor feedback on climate stability;
High latitude tropospheric-stratospheric exchange processes related to polar vortex conditions;
Climatology of Rossby waves and atmospheric internal waves.
EUMETSAT GRAS SAF 2nd User Workshop 2003
8
esa
Satellite Constellation
•
4 micro-satellites
•
•
•
Stable two-plane constellation in 90
degrees inclination
•
•
To optimize the temporal and local time
distribution of occultations
Instruments
•
•
EUMETSAT GRAS SAF 2nd User Workshop 2003
Heights 650 km and 850 km – to optimize
spatial distribution of occultations
Orbital local time drift
•
•
In each plane, counter-rotating orbits with
2 satellites - for optimizing quality of
measurements
Two altitudes
•
•
Mass: 130 kg
Power: 80 W
L-band GPS/GALILEO precision receiver
X/K-band LEO-LEO precision transmitter
and receiver (2 of each)
9
esa
CALL FORE
Antennas
CALL
Transmitter
CALL AFT
Antennas
CALL FORE
GRAS FORE
Antenna
GRAS
Electronics
CALL AFT
Antennas
CALL Receiver
Antennas
USO
USO
GRAS AFT
Antenna
GRAS FORE
Antenna
GRAS
Electronics
GRAS AFT
Antenna
GRAS Zenith
Antenna
GRAS Zenith
Antenna
EUMETSAT GRAS SAF 2nd User Workshop 2003
10
esa
Why is measurements of
atmospheric water vapor important ?
•
•
•
•
•
•
•
Indicator of climate change
Strongest greenhouse gas
Climate positive/negative feedback
Energy reservoir
Impact/feedback on global wind system
changes and general atmosphere
dynamics
Hydrologic cycle
Highly variable (time and space)
EUMETSAT GRAS SAF 2nd User Workshop 2003
11
esa
Global Temperature Deviations
EUMETSAT GRAS SAF 2nd User Workshop 2003
12
esa
Forcing residuals in atmospheric models
Estimation of the residual (R) requires availability of high quality observed data.
Forcing residuals can be used to:
•
•
identify tendency errors in the differential equations of atmospheric models
detect temporal variations in external forcing of the atmosphere.
EUMETSAT GRAS SAF 2nd User Workshop 2003
13
esa
Weak nudging towards the re-analyses
Data assimilation via nudging:
     obs   MOD
t
t

*
Discretization in time (assimilation in spectral space):
n ,m (t  t )  n*,m (t  t )
 2t
(nERA
, m (t  t )  n , m (t  t ))

Forcing residual is approximated by the last fraction:
Rn,m (t  t ) 
(nERA
, m (t  t )  n , m (t  t ))
EUMETSAT GRAS SAF 2nd User Workshop 2003

14
esa
The ACE+ Experiment
EUMETSAT GRAS SAF 2nd User Workshop 2003
15
esa
GRAS+ Temperature Retrieval
EUMETSAT GRAS SAF 2nd User Workshop 2003
16
esa
Processing Steps for Water Vapor Retrievals
EUMETSAT GRAS SAF 2nd User Workshop 2003
17
esa
GRAS+ Requirements
Parameter
Temperature
Humidity
Horizontal domain
Global
Global
Horizontal sampling
1.0x1.0 - 2.5x2.5
1.0x1.0 - 2.5x2.5
Vertical domain
Boundary Layer - 1 hPa
(0 - 50 km)
Boundary Layer - 300 hPa
(0 - 10 km)
Vertical
Resolution
Troposphere
0.5 km
0.5 km
Stratosphere
1 km
–
Time domain
> 5 years
> 5 years
Time resolution
1 - 10 years
1 - 10 years
Long-term stability
< 0.1 K/decade
< 2% RH/decade
Number of profiles per grid
box per month
> 40
> 40
Accuracy
Troposphere
<1K
< 10%
Stratosphere
<1K
–
Timeliness (NWP)
3 hrs
3 hrs
Timeliness (Climate)
30–60 days
30–60 days
EUMETSAT GRAS SAF 2nd User Workshop 2003
18
esa
Absorption at X/K-band frequencies
Water Vapor Absorption
0.30
Frequencies:
Absorptivity (dB km-1)
0.25
10.0-11.5 GHz
17.2-17.3 GHz
22.5-23.5 GHz
0.20
0.15
100%
0.10
75%
50%
0.05
0.00
0
25%
3%
10
20
Frequency (GHz)
10%
0%
30
EUMETSAT GRAS SAF 2nd User Workshop 2003
40
19
esa
Absorption
EUMETSAT GRAS SAF 2nd User Workshop 2003
20
esa
CALL Temperature and Humidity Retrieval
EUMETSAT GRAS SAF 2nd User Workshop 2003
21
esa
CALL
Temperature
and Humidity
Requirements
Parameter
Specific Humidity
Temperature
Horizontal Domain
Global
Global
Horizontal Sampling
100–500 km
100–500 km
Vertical Domain
Surface to 10 hPa
Surface to 100 hPa
Vertical
LT
0.4–2 km
0.3–3 km
Sampling
HT
0.5–2 km
1–3 km
LS
–
1–3 km
HS
–
5–10 km
3–24 hrs
3–24 hrs
Time Sampling
RMS
LT
0.25–1 g/kg
0.5–3 K
Accuracy
HT
0.025–0.1 g/kg
0.5–3 K
LS
–
0.5–3 K
HS
–
1–3K
Timeliness (NWP)
1–3 hrs
1–3 hrs
Timeliness (Climate)
30–60 days
30–60 days
Time Domain (Climate)
> 5 years
> 5 years
Long-term Stability
< 2% RH/decade
< 0.1 K/decade
> 40
> 40
No. of profiles/
grid box/month
EUMETSAT GRAS SAF 2nd User Workshop 2003
22
esa
Weekly Profile Coverage
Weekly latitudinal distribution of occultations. Longitudinal variations still exist in
the seven days simulation. Part of the spread in the plot is due to this effect.
Average time difference (min) between profiles in each cell as function of latitude.
The simulation covers a whole week of data.
For the 500 x 500 km cells the following statistics can be calculated:
Average number of occultations in a cell: 22.49
Standard deviation: 10.36
Average time difference between the occultations: 482 min [8h 2min]
Standard deviation: 216 min [3h 36min]
EUMETSAT GRAS SAF 2nd User Workshop 2003
23
esa
Global Distribution of Occultations
EUMETSAT GRAS SAF 2nd User Workshop 2003
24
esa
Distribution of NWP Radiosonde Observations
EUMETSAT GRAS SAF 2nd User Workshop 2003
25
esa
Global Distribution of LEO-LEO Occultations
EUMETSAT GRAS SAF 2nd User Workshop 2003
26
esa
Global Humidity Fields
EUMETSAT GRAS SAF 2nd User Workshop 2003
27
esa
•
Launch
•
•
Mission lifetime
•
EUMETSAT GRAS SAF 2nd User Workshop 2003
2006/2007
5 years (2006 – 2012)
28